A hybrid tabu search/set partitioning approach to tanker crew scheduling

Aerial refueling is a crucial component of modern day military operations. A vital part of this refueling process is the individual tanker crew. Constrained by the number of tanker crews available, the United States Air Force must find ways to efficiently schedule them. This paper discusses an effective hybrid tabu search/set partitioning approach to Air Mobility Command's tanker crew scheduling problem. This hybrid approach combines the metaheuristic tabu search with a classical optimization approach. A novel, dynamic, neighborhood-based vocabulary scheme is developed to exploit a set-partition based optimizer. The results show that the hybrid approach significantly outperforms the tabu search alone. The robustness of the developed approach is judged with testing using designed experiments. Finally, an integer program (IP) is developed to calculate lower bounds for the tanker crew scheduling problem objectives and to measure the overall quality of solutions produced by the hybrid approach.